Feasibility of contour mapping epidemiological data with missing values

Data of epidemiologic interest often occur as spatial information during each of several time periods. In most cases data are available from a set of regions or localities which can be viewed as points in a plane. Although contour mapping is useful for displaying these data, the lack of data for all data points in a region may lead to erroneous interpretation. In this paper we use stimulation to investigate the impact of missing data points for contour mapping using two distinct simulated spatial-time distributions for epidemiologic variables. A model for the occurrence of malaria in localities randomly distributed in one region is chosen as the prototype for data generation.